AI Security
Know every AI asset across accounts, then harden inference: prompt injection, PII leakage, hallucinations, and regulated model deployment.
AI workloads add four control surfaces traditional compliance frameworks did not contemplate: knowing what AI exists across accounts (Security Hub AI inventory — managed Bedrock/AgentCore/SageMaker via Config, self-hosted stacks via Inspector SBOM, external model APIs via GuardDuty DNS), prompt-injection and PII leakage in inference paths, training-data lineage and consent, and model governance. The guides below cover inventory-backed discovery, Bedrock Guardrails (PII redaction, text and image content filters, denied topics, word filters, contextual grounding, and Automated Reasoning checks — all HIPAA-eligible), HIPAA-eligible AI architectures including Bedrock AgentCore, and GenAI governance for regulated industries.
Part of the AWS Security & Compliance hub.
Guides
Amazon Bedrock Guardrails protect foundation models from harmful outputs — filtering on prompt injection, jailbreaks, toxicity, and PII. This guide covers setup, testing, cost optimization, and production safety patterns for GenAI applications.
Production guide for HIPAA-compliant generative AI on AWS Bedrock — BAA scope, eligible models, Guardrails for PHI redaction, Knowledge Bases for RAG over clinical data, VPC isolation, and the audit evidence package OCR investigators expect.
Deploying GenAI without guardrails is a compliance incident waiting to happen. Here is how to build a production-grade AI governance layer on AWS using Amazon Bedrock Guardrails, least-privilege IAM, and continuous evaluation.
Bedrock Automated Reasoning checks ground LLM outputs against formal logic policies you encode and mathematically validate that the response is consistent with the policy. This guide covers when to use Automated Reasoning vs contextual grounding, how to author the policy in production, the integration with Bedrock Guardrails, and the regulated use cases (HR, insurance, eligibility, regulatory determinations) where the difference matters.
AWS Security Hub aggregates security findings from 200+ sources and, as of Jul 14 2026, includes AI inventory for org-wide AI assets. This guide covers setup, compliance standards, AI inventory, automated remediation, and a compliance dashboard without hiring a SOC team.
Services
Engagements where we apply the patterns above to your specific environment, regulatory scope, and threat model.
Secure your AWS environment before deploying AI. Free Cyber-Led AI Readiness Check covers IAM, SageMaker, S3, and GPU risks. SMB-focused. Fix in weeks.
Cloud compliance services — HIPAA, SOC 2, PCI DSS, ISO 27001, GDPR. Expert consulting from FactualMinds.
Related subtopics
Sibling subtopics that buyers usually evaluate alongside this one.
Framework-by-framework guidance — what auditors expect, what AWS provides, and what your team configures.
Bucket-level controls, secret rotation, KMS post-quantum, Amazon Macie for data classification, and clean-room collaboration without raw-data sharing.
Continuous monitoring, Security Hub AI inventory, agentless vulnerability scanning, OCSF data lakes, and automated remediation.
FAQ
Our consulting engagements apply this guidance to your specific environment, regulatory scope, and threat model.